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IJSRP, Volume 9, Issue 5, May 2019 Edition [ISSN 2250-3153]



      Vincent Camara

Abstract: Rules about the mean of a Gaussian distribution are presented and compared. Considering the square error loss function, our approximate Bayesian decision rule for the mean of a normal population is derived. Using normal data and SAS software, our approximate Bayesian test results were compared to their classical counterparts obtained with the well-known classical decision rule. It is shown that the proposed approximate Bayesian decision rule relies only on observations that are under study. The classical decision rule, which uses the standard normal and the student-t statistics, does not always yield the best results; the proposed approach performs often

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Vincent Camara (2019); A New Approximate Bayesian Decision Rule About the Mean of a Gaussian Distribution Versus the Classical Decision Rule; International Journal of Scientific and Research Publications (IJSRP) 9(5) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.9.05.2019.p89111

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